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Canonical Face Embeddings
When instead evaluating embeddings generated from two CNNs, where one CNN's embeddings are mapped with a linear transformation, the mean true accept rate drops to 0. 95 using the same verification paradigm.
Exploring the Interchangeability of CNN Embedding Spaces
When image embeddings generated by one CNN are transformed into embeddings corresponding to the feature space of a second CNN trained on the same task, their respective image classification or face verification performance is largely preserved.
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